In-class Exercise 3

A new article created using the Distill format.

Write a code chunk to check, install and launch the following R packages:

packages = c('ggiraph','plotly', 'DT',
             'patchwork', 'gganimate', 
             'tidyverse', 'readxl', 'gifski',
             'gapminder')
for (p in packages) {
  if (!require(p, character.only = T)){
    install.packages(p)
  }
  library(p, character.only = T)
}

Using read_csv() of readr package, import Exam_data.csv into R.

exam_data <- read_csv("data/Exam_data.csv")

p <- ggplot(data=exam_data,    #output as object p
            aes(x = MATHS)) +
geom_dotplot_interactive(
  aes(tooltip = ID),       #show ID when hover over
  stackgroups = TRUE,
  binwidth = 1,
  method = "histodot") +
scale_y_continuous(NULL,
                   breaks = NULL)
girafe(          #use girafe to make it interactive
  ggobj = p,
  width_svg = 6,
  height_svg = 6*0.618
)

p <- ggplot(data=exam_data,
            aes(x = MATHS)) +
  geom_dotplot_interactive(
    aes(data_id = CLASS,   #highlight the students in same class when hover over the dot
        tooltip = ID),
    stackgroups = TRUE,
    binwidth = 1,
    method = "histodot") +
  scale_y_continuous(NULL,
                     breaks = NULL)
girafe(
  ggobj = p,
  width_svg = 6,
  height_svg = 6*0.618,
  options = list(
    opts_hover(css = "fill: #202020;"),
    opts_hover_inv(css = "opacity:0.2;")
    )
)

p1 <- ggplot(data=exam_data,
             aes(x = MATHS)) +
  geom_dotplot_interactive(
    aes(data_id = ID,
        tooltip = ID),
    stackgroups = TRUE,
    binwidth = 1,
    method = "histodot") +
  coord_cartesian(xlim=c(0,100)) +
  scale_y_continuous(NULL,
                     breaks = NULL)

p2 <- ggplot(data=exam_data,
             aes(x = ENGLISH)) +
  geom_dotplot_interactive(
    aes(data_id = ID,
        tooltip = ID),
    stackgroups = TRUE,
    binwidth = 1,
    method = "histodot") +
  coord_cartesian(xlim=c(0,100)) +
  scale_y_continuous(NULL,
                     breaks = NULL)

girafe(code = print(p1 / p2), #patchwork function
       width_svg = 6,
       height_svg = 6,
       options = list(
         opts_hover(css = "fill: #202020;"),
         opts_hover_inv(css = "opacity:0.2;")
         )
       )

pal <- c("red", "purple", "blue", "green")
plot_ly(data = exam_data,
        x = ~MATHS,
        y = ~ENGLISH,
        text = ~paste("Student ID:",
                      ID,"<br>Class:", CLASS),  #br means to break line
        color = ~RACE,
        colors = pal)

plot_ly(data = exam_data,
        x = ~ENGLISH,
        y = ~MATHS,
        text = ~paste("Student ID:", ID,
                      "<br>Class:", CLASS),
        color = ~RACE,
        colors = "Set1") %>%
layout(title = 'English Score versus Maths Score',
       xaxis = list(range = c(0, 100, 20)),
       yaxis = list(range = c(0, 100, 20)))

d <- highlight_key(exam_data)
p1 <- ggplot(data=d,
             aes(x = MATHS,
                 y = ENGLISH)) +
  geom_point(size=1) +
  coord_cartesian(xlim=c(0,100),
                  ylim=c(0,100))
p2 <- ggplot(data=d,
             aes(x = MATHS,
                 y = SCIENCE)) +
  geom_point(size=1) +
  coord_cartesian(xlim=c(0,100),
                  ylim=c(0,100))
subplot(ggplotly(p1),
        ggplotly(p2))

p1 <- ggplot(data=exam_data,
             aes(x = MATHS,
                 y = ENGLISH)) +
  geom_point(size=1) +
  coord_cartesian(xlim=c(0,100),
                  ylim=c(0,100))
p2 <- ggplot(data=exam_data,
             aes(x = MATHS,
                 y = SCIENCE)) +
  geom_point(size=1) +
  coord_cartesian(xlim=c(0,100),
                  ylim=c(0,100))
subplot(ggplotly(p1),
        ggplotly(p2))

DT::datatable(exam_data)

d <- highlight_key(exam_data)
p <- ggplot(d,
            aes(ENGLISH,
                MATHS)) +
  geom_point(size=1) +
  coord_cartesian(xlim=c(0,100),
                  ylim=c(0,100))
gg <- highlight(ggplotly(p),
                "plotly_selected")
crosstalk::bscols(gg,
                  DT::datatable(d),
                  widths = 5)